104 research outputs found

    A 3D End-Effector Robot for Upper Limb Functional Rehabilitation of Hemiparesis Patients

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    Robot-assisted therapy is a new type of rehabilitation that allows for highly repetitive, intensive, adaptable, and quantifiable physical training. It is increasingly being used to restore motor function, particularly in stroke survivors with upper limb paresis. The end-effector type robot allows natural movements without complex structure which is ideal for functional rehabilitation training. A 3D end-effector base on a five-bar linkage has been proposed to improve the common end-effector type that covers mechanical design, dynamic control strategy, and application of rehabilitation training or exercise. The dynamic controllers are deweighting with gravity compensation, passive mobilization or active assistive, and the virtual spring-damper wall concept. These controllers are used for developing functional rehabilitation training or exercise from an engineering point of view based on experiences in developing various types of rehabilitation robots. The experiments, based on the performance of the controllers, have been conducted with healthy subjects. The experimental results have shown very promising results and can be extended to various types of functional rehabilitation

    Design, Fabrication, and Control of an Upper Arm Exoskeleton Assistive Robot

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    Stroke is the primary cause of permanent impairment and neurological damage in the United States and Europe. Annually, about fifteen million individuals worldwide suffer from stroke, which kills about one third of them. For many years, it was believed that major recovery can be achieved only in the first six months after a stroke. More recent research has demonstrated that even many years after a stroke, significant improvement is not out of reach. However, economic pressures, the aging population, and lack of specialists and available human resources can interrupt therapy, which impedes full recovery of patients after being discharged from hospital following initial rehabilitation. Robotic devices, and in particular portable robots that provide rehabilitation therapy at home and in clinics, are a novel way not only to optimize the cost of therapy but also to let more patients benefit from rehabilitation for a longer time. Robots used for such purposes should be smaller, lighter and more affordable than the robots currently used in clinics and hospitals. The common human-machine interaction design criteria such as work envelopes, safety, comfort, adaptability, space limitations, and weight-to-force ratio must still be taken into consideration.;In this work a light, wearable, affordable assistive robot was designed and a controller to assist with an activity of daily life (ADL) was developed. The mechanical design targeted the most vulnerable group of the society to stroke, based on the average size and age of the patients, with adjustability to accommodate a variety of individuals. The novel mechanical design avoids motion singularities and provides a large workspace for various ADLs. Unlike similar exoskeleton robots, the actuators are placed on the patient\u27s torso and the force is transmitted through a Bowden cable mechanism. Since the actuators\u27 mass does not affect the motion of the upper extremities, the robot can be more agile and more powerful. A compact novel actuation method with high power-to-weight ratio called the twisted string actuation method was used. Part of the research involved selection and testing of several string compositions and configurations to compare their suitability and to characterize their performance. Feedback sensor count and type have been carefully considered to keep the cost of the system as low as possible. A master-slave controller was designed and its performance in tracking the targeted ADL trajectory was evaluated for one degree of freedom (DOF). An outline for proposed future research will be presented

    A fairly simple mechatronic device for training human wrist motion

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    This article proposes a novel device for wrist motion rehabilitation. The proposed mechatronic architecture is based on a simple user-friendly design, which includes a mobile platform for hand support, which is operated by a single actuator. A dedicated assist-as-needed control is designed to operate the device for the required movements. The proposed control strategy is also integrated into a gaming software for stimulating the exercising by means of various interactions with patients. Experimental tests are carried out with 14 healthy subjects at the Physiotherapy Clinical Hospital of the Federal University of Uberlandia. Also, three patients with stroke have been enrolled in a pilot clinical testing. Each of the patients has been involved in four sessions per month with 15 min of assisted treatment. Results of experimental tests are analyzed in terms of improvements and amplitude gains for the flexion and extension wrist movements. Experimental results are reported as evidence for the feasibility and soundness of the proposed device as a tool to assist professionals in procedures of wrist rehabilitation

    Nonlinear control of a seven degrees-of-freedom exoskeleton robot arm

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    Advances in the field of robotics have allowed increasingly integrating robotic devices for rehabilitation of physical disabilities. This research work is encompassed into the field of rehabilitation robotics; it presents the development of the robot ETS-MARSE, a seven degrees-of-freedom exoskeleton designed to be worn in the human arm. The developments include the study and implementation of a relatively novel nonlinear control approach, as well as different rehabilitation schemes. One of the characteristics of a rehabilitation robot is that it deals with a wide number of patients that have different biomechanical and physiological conditions. The implementation of the nonlinear control technique known as Virtual Decomposition Control addresses this issue with its internal parameters’ adaptation that presents a robust behavior to different characteristics of the robot users. Besides, this technique simplifies the complexity of high degree-of-freedom robots by its innovative sub-systems decomposition. All of above, while ensuring the system asymptotic stability and excellent trajectory tracking. Between the different rehabilitation schemes, we can mention: passive, active-assistive and active rehabilitation. The first one follows predefined trajectories and relies on the efficiency of the controller. The two other schemes require understanding the user’s intention of movement and take an action in order to guide, restrain, correct or follow it. For this purpose, we present an approach that utilizes a force sensor as the human-robot interface in order to transform, via an admittance function, the forces that the user exert to the robot end-effector (handle), and execute active-assisted or active rehabilitation. Finally among the main developments of this work, an approach is presented in which the need of a force sensor to perform some active rehabilitation tasks is removed. By means of a nonlinear observer, the interaction forces are estimated and the user’s intention of movement followed. Experimental results show the effectiveness of all the proposed approaches. All the tests involving humans were tested with healthy subjects. Trajectory tracking of the robot is executed in joint space; some trajectories are given in Cartesian space and transformed to joint space by means of the pseudoinverse of the Jacobian technique. However this option is limited; a mandatory next step to improve many functionalities of the robot is to solve its inverse kinematics. Between other progresses that are in development, is an approach to process electromyographic signals in order to obtain information from the robot’s users. First results on this methodology are presented. Teleoperation and haptic capabilities are also in the initial stage of development

    Upper-Limb Kinematic Parameter Estimation and Localization Using a Compliant Robotic Manipulator

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    Assistive and rehabilitation robotics have gained momentum over the past decade and are expected to progress significantly in the coming years. Although relevant and promising research advances have contributed to these fields, challenges regarding intentional physical contact with humans remain. Despite being a fundamental component of assistive and rehabilitation tasks, there is an evident lack of work related to robotic manipulators that intentionally manipulate human body parts. Moreover, existing solutions involving end-effector robots are not based on accurate knowledge of human limb dimensions and their current configuration. This knowledge, which is essential for safe human–limb manipulation, depends on the grasping location and human kinematic parameters. This paper addresses the upper-limb manipulation challenge and proposes a pose estimation method using a compliant robotic manipulator. To the best of our knowledge, this is the first attempt to address this challenge. A kinesthetic-based approach enables estimation of the kinematic parameters of the human arm without integrating external sensors. The estimation method relies only on proprioceptive data obtained from a collaborative robot with a Cartesian impedance-based controller to follow a compliant trajectory that depends on human arm kinodynamics. The human arm model is a 2-degree of freedom (DoF) kinematic chain. Thus, prior knowledge of the arm's behavior and an estimation method enables estimation of the kinematic parameters. Two estimation methods are implemented and compared: i) Hough transform (HT); ii) least squares (LS). Furthermore, a resizable, sensorized dummy arm is designed for experimental validation of the proposed approach. Outcomes from six experiments with different arm lengths demonstrate the repeatability and effectiveness of the proposed methodology, which can be used in several rehabilitation robotic applications

    Kinematics and Robot Design IV, KaRD2021

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    This volume collects the papers published on the special issue “Kinematics and Robot Design IV, KaRD2021” (https://www.mdpi.com/journal/robotics/special_issues/KaRD2021), which is the forth edition of the KaRD special-issue series, hosted by the open-access journal “MDPI Robotics”. KaRD series is an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2021, after the peer-review process, accepted 12 papers. The accepted papers cover some theoretical and many design/applicative aspects

    Robotic Platforms for Assistance to People with Disabilities

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    People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks

    Robotic Home-Based Rehabilitation Systems Design: From a Literature Review to a Conceptual Framework for Community-Based Remote Therapy During COVID-19 Pandemic

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    During the COVID-19 pandemic, the higher susceptibility of post-stroke patients to infection calls for extra safety precautions. Despite the imposed restrictions, early neurorehabilitation cannot be postponed due to its paramount importance for improving motor and functional recovery chances. Utilizing accessible state-of-the-art technologies, home-based rehabilitation devices are proposed as a sustainable solution in the current crisis. In this paper, a comprehensive review on developed home-based rehabilitation technologies of the last 10 years (2011–2020), categorizing them into upper and lower limb devices and considering both commercialized and state-of-the-art realms. Mechatronic, control, and software aspects of the system are discussed to provide a classified roadmap for home-based systems development. Subsequently, a conceptual framework on the development of smart and intelligent community-based home rehabilitation systems based on novel mechatronic technologies is proposed. In this framework, each rehabilitation device acts as an agent in the network, using the internet of things (IoT) technologies, which facilitates learning from the recorded data of the other agents, as well as the tele-supervision of the treatment by an expert. The presented design paradigm based on the above-mentioned leading technologies could lead to the development of promising home rehabilitation systems, which encourage stroke survivors to engage in under-supervised or unsupervised therapeutic activities

    Design and Control of Robotic Systems for Lower Limb Stroke Rehabilitation

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    Lower extremity stroke rehabilitation exhausts considerable health care resources, is labor intensive, and provides mostly qualitative metrics of patient recovery. To overcome these issues, robots can assist patients in physically manipulating their affected limb and measure the output motion. The robots that have been currently designed, however, provide assistance over a limited set of training motions, are not portable for in-home and in-clinic use, have high cost and may not provide sufficient safety or performance. This thesis proposes the idea of incorporating a mobile drive base into lower extremity rehabilitation robots to create a portable, inherently safe system that provides assistance over a wide range of training motions. A set of rehabilitative motion tasks were established and a six-degree-of-freedom (DOF) motion and force-sensing system was designed to meet high-power, large workspace, and affordability requirements. An admittance controller was implemented, and the feasibility of using this portable, low-cost system for movement assistance was shown through tests on a healthy individual. An improved version of the robot was then developed that added torque sensing and known joint elasticity for use in future clinical testing with a flexible-joint impedance controller
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